Gender Differences in Objective and Subjective Social Isolation and Self-Reported Hypertension in Older Adults
Bibliographic record
Abstract
Hypertension is a major public health concern, especially in older adults, and gender differences are a factor in terms of its prevalence. Social connections benefit health, while social isolation is linked to negative outcomes. Prior studies suggest social isolation and connectedness vary by gender, but few have explored this relationship with hypertension. This study examined gender differences in the association between social isolation and hypertension in older adults using data from the National Survey of American Life (1280 adults aged ≥55). Weighted logistic regressions tested gender differences in objective and subjective social isolation and hypertension. Both men and women who were objectively isolated from family and friends, or only friends, were less likely to have hypertension than those not isolated. However, when accounting for subjective isolation, only isolation from family predicted hypertension. Gender moderated this relationship-men isolated from family and friends had a higher likelihood of hypertension, while no such association was found for women. Findings suggest that preventing objective isolation, particularly from family, may help reduce hypertension risk in older adults. This study highlights the need to further investigate social isolation's impact on health and its underlying mechanisms among older adults in the U.S.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".